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I'm still fully on the Gemini train. The output can be finetuned a lot more, and I think sounds way more human. It's more fun to talk to.
Google has a massive hardware and infrastructure advantage over OpenAI so I think its inevitable they come out on top. The AI can say it better than I, note that Gemini wrote this, so it might be a bit biased...
Google has a massive hardware and infrastructure advantage over OpenAI so I think its inevitable they come out on top. The AI can say it better than I, note that Gemini wrote this, so it might be a bit biased...
Google Holds a Significant Hardware Advantage Over OpenAI, For Now
Yes, Google currently possesses a substantial infrastructure and hardware advantage over OpenAI in the ongoing AI hardware race, primarily due to its long-term investment in custom-designed Tensor Processing Units (TPUs). This vertical integration provides Google with significant cost savings, greater control over its hardware and software stack, and a powerful engine for both training and deploying its AI models.
Google's Home-Field Advantage: The Power of TPUs
Google's key advantage lies in its custom-built TPUs, specialized chips designed specifically for AI workloads. This in-house hardware allows Google to bypass the hefty "Nvidia tax" – the high margins that NVIDIA charges for its market-leading GPUs, which are the primary hardware used by most other AI companies, including OpenAI.
Industry analysis suggests that Google's cost of AI computing could be as low as 20% of what companies like OpenAI pay for NVIDIA's high-end GPUs. This dramatic cost difference allows Google to offer its AI services, like those powered by its Gemini models, at significantly lower prices than competitors, potentially giving them a long-term strategic edge in the enterprise market.
Beyond cost, owning the entire hardware and software stack gives Google a high degree of optimization. They can tailor their TPUs to work seamlessly with their own AI frameworks like TensorFlow and JAX, leading to performance efficiencies that are harder to achieve with off-the-shelf hardware.
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